Generation of synthetic context objects using bounded context objects

ABSTRACT

A computer-implemented method, system, and/or computer program product generates and utilizes synthetic context-based objects. One or more processors define a context object, where the context object provides a context that identifies a specific subject-matter, from multiple subject-matters, of a non-contextual data object. The processor(s) associate the non-contextual data object with the context object to define a synthetic context-based object and the synthetic context-based object with at least one specific data store. A request is received from a requester for data from said at least one specific data store that is associated with the synthetic context-based object, where said at least one specific data store is within a database of multiple data stores. Data is returned to the requester from said at least one specific data store that is associated with the synthetic context-based object.

BACKGROUND

The present disclosure relates to the field of computers, andspecifically to the use of databases in computers. Still moreparticularly, the present disclosure relates to a context-baseddatabase.

A database is a collection of data. Examples of database types includerelational databases, graph databases, network databases, andobject-oriented databases. Each type of database presents data in anon-dynamic manner, in which the data is statically stored.

SUMMARY

In one embodiment of the present invention, a processor-implementedmethod, system, and/or computer program product generates and utilizessynthetic context-based objects. One or more processors define a contextobject, where the context object provides a context that identifies aspecific subject-matter, from multiple subject-matters, of anon-contextual data object, and where the non-contextual data objectambiguously relates to one or more of the multiple subject-matters. Theprocessor(s) associate the non-contextual data object with the contextobject to define a synthetic context-based object and the syntheticcontext-based object with at least one specific data store, where saidat least one specific data store is a data repository of data that isrelevant to a context of the synthetic context-based object, and wherethe specific subject-matter for said at least one specific data store ina data structure overlaps a subject-matter of another data store in thedata structure. A request is received from a requester for data fromsaid at least one specific data store that is associated with thesynthetic context-based object, where said at least one specific datastore is within a database of multiple data stores. Data is returned tothe requester from said at least one specific data store that isassociated with the synthetic context-based object.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an exemplary system and network in which the presentdisclosure may be implemented;

FIG. 2 illustrates a process for generating one or more syntheticcontext-based objects;

FIG. 3 depicts an exemplary case in which synthetic context-basedobjects are defined for the non-contextual data object datum “Rock”;

FIG. 4 illustrates an exemplary case in which synthetic context-basedobjects are defined for the non-contextual data object data “104-106”;

FIG. 5 depicts an exemplary case in which synthetic context-basedobjects are defined for the non-contextual data object datum “Statin”;

FIG. 6 illustrates a process for associating one or more data storeswith specific synthetic context-based objects;

FIG. 7 depicts a process for locating a particular data store via auser-selected synthetic context-based object;

FIG. 8 illustrates an exemplary hierarchical constraint-bound contextobject; and

FIG. 9 is a high-level flow chart of one or more steps performed by acomputer processor to generate and utilize synthetic context-basedobjects to locate and/or return specific data stores to a requester.

DETAILED DESCRIPTION

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including, but not limited to, wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of thepresent invention. It will be understood that each block of theflowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

With reference now to the figures, and in particular to FIG. 1, there isdepicted a block diagram of an exemplary system and network that may beutilized by and in the implementation of the present invention. Notethat some or all of the exemplary architecture, including both depictedhardware and software, shown for and within computer 102 may be utilizedby software deploying server 150, a data storage system 152, and/or auser computer 154.

Exemplary computer 102 includes a processor 104 that is coupled to asystem bus 106. Processor 104 may utilize one or more processors, eachof which has one or more processor cores. A video adapter 108, whichdrives/supports a display 110, is also coupled to system bus 106. Systembus 106 is coupled via a bus bridge 112 to an input/output (I/O) bus114. An I/O interface 116 is coupled to I/O bus 114. I/O interface 116affords communication with various I/O devices, including a keyboard118, a mouse 120, a media tray 122 (which may include storage devicessuch as CD-ROM drives, multi-media interfaces, etc.), a printer 124, andexternal USB port(s) 126. While the format of the ports connected to I/Ointerface 116 may be any known to those skilled in the art of computerarchitecture, in one embodiment some or all of these ports are universalserial bus (USB) ports.

As depicted, computer 102 is able to communicate with a softwaredeploying server 150, using a network interface 130. Network interface130 is a hardware network interface, such as a network interface card(NIC), etc. Network 128 may be an external network such as the Internet,or an internal network such as an Ethernet or a virtual private network(VPN).

A hard drive interface 132 is also coupled to system bus 106. Hard driveinterface 132 interfaces with a hard drive 134. In one embodiment, harddrive 134 populates a system memory 136, which is also coupled to systembus 106. System memory is defined as a lowest level of volatile memoryin computer 102. This volatile memory includes additional higher levelsof volatile memory (not shown), including, but not limited to, cachememory, registers and buffers. Data that populates system memory 136includes computer 102's operating system (OS) 138 and applicationprograms 144.

OS 138 includes a shell 140, for providing transparent user access toresources such as application programs 144. Generally, shell 140 is aprogram that provides an interpreter and an interface between the userand the operating system. More specifically, shell 140 executes commandsthat are entered into a command line user interface or from a file.Thus, shell 140, also called a command processor, is generally thehighest level of the operating system software hierarchy and serves as acommand interpreter. The shell provides a system prompt, interpretscommands entered by keyboard, mouse, or other user input media, andsends the interpreted command(s) to the appropriate lower levels of theoperating system (e.g., a kernel 142) for processing. Note that whileshell 140 is a text-based, line-oriented user interface, the presentinvention will equally well support other user interface modes, such asgraphical, voice, gestural, etc.

As depicted, OS 138 also includes kernel 142, which includes lowerlevels of functionality for OS 138, including providing essentialservices required by other parts of OS 138 and application programs 144,including memory management, process and task management, diskmanagement, and mouse and keyboard management.

Application programs 144 include a renderer, shown in exemplary manneras a browser 146. Browser 146 includes program modules and instructionsenabling a world wide web (WWW) client (i.e., computer 102) to send andreceive network messages to the Internet using hypertext transferprotocol (HTTP) messaging, thus enabling communication with softwaredeploying server 150 and other computer systems.

Application programs 144 in computer 102's system memory (as well assoftware deploying server 150's system memory) also include a syntheticcontext-based object processing logic (SCBOPL) 148. SCBOPL 148 includescode for implementing the processes described below, including thosedescribed in FIGS. 2-8. In one embodiment, computer 102 is able todownload SCBOPL 148 from software deploying server 150, including in anon-demand basis, wherein the code in SCBOPL 148 is not downloaded untilneeded for execution. Note further that, in one embodiment of thepresent invention, software deploying server 150 performs all of thefunctions associated with the present invention (including execution ofSCBOPL 148), thus freeing computer 102 from having to use its owninternal computing resources to execute SCBOPL 148.

The data storage system 152 stores an electronic data structure, whichmay be audio files, video files, website content, text files, etc. Inone embodiment, computer 102 contains the synthetic context-based objectdatabase described herein, while data storage system 152 contains thenon-contextual data object database, context object database, and datastructure described herein. For example, in one embodiment, syntheticcontext-based object database 202 depicted in FIG. 2 is stored in asynthetic context-based object database storage system, which is part ofthe hard drive 134 and/or system memory 136 of computer 102 and/or datastorage system 152; non-contextual data object database 206 depicted inFIG. 2 is stored in a non-contextual data object database storagesystem, which is part of the hard drive 134 and/or system memory 136 ofcomputer 102 and/or data storage system 152; context object database 210depicted in FIG. 2 is stored in a context object database storagesystem, which is part of the hard drive 134 and/or system memory 136 ofcomputer 102 and/or data storage system 152; and data structure 302depicted in FIG. 3 is stored in a data structure storage system, whichis part of the hard drive 134 and/or system memory 136 of computer 102and/or data storage system 152.

Note that the hardware elements depicted in computer 102 are notintended to be exhaustive, but rather are representative to highlightessential components required by the present invention. For instance,computer 102 may include alternate memory storage devices such asmagnetic cassettes, digital versatile disks (DVDs), Bernoullicartridges, and the like. These and other variations are intended to bewithin the spirit and scope of the present invention.

Note that SCBOPL 148 is able to generate and/or utilize some or all ofthe databases depicted in the context-based system in FIGS. 2-7.

With reference now to FIG. 2, a process for generating one or moresynthetic context-based objects in a system 200 is presented. Note thatsystem 200 is a processing and storage logic found in computer 102and/or data storage system 152 shown in FIG. 1, which process, support,and/or contain the databases, pointers, and objects depicted in FIG. 2.

Within system 200 is a synthetic context-based object database 202,which contains multiple synthetic context-based objects 204 a-204 n(thus indicating an “n” quantity of objects, where “n” is an integer).Each of the synthetic context-based objects 204 a-204 n is defined by atleast one non-contextual data object and at least one context object.That is, at least one non-contextual data object is associated with atleast one context object to define one or more of the syntheticcontext-based objects 204 a-204 n. The non-contextual data objectambiguously relates to multiple subject-matters, and the context objectprovides a context that identifies a specific subject-matter, from themultiple subject-matters, of the non-contextual data object.

Note that the non-contextual data objects contain data that has nomeaning in and of itself. That is, the data in the context objects arenot merely attributes or descriptors of the data/objects described bythe non-contextual data objects. Rather, the context objects provideadditional information about the non-contextual data objects in order togive these non-contextual data objects meaning. Thus, the contextobjects do not merely describe something, but rather they define whatsomething is. Without the context objects, the non-contextual dataobjects contain data that is meaningless; with the context objects, thenon-contextual data objects become meaningful.

For example, assume that a non-contextual data object database 206includes multiple non-contextual data objects 208 r-208 t (thusindicating a “t” quantity of objects, where “t” is an integer). However,data within each of these non-contextual data objects 208 r-208 t byitself is ambiguous, since it has no context. That is, the data withineach of the non-contextual data objects 208 r-208 t is data that,standing alone, has no meaning, and thus is ambiguous with regards toits subject-matter. In order to give the data within each of thenon-contextual data objects 208 r-208 t meaning, they are given context,which is provided by data contained within one or more of the contextobjects 210 x-210 z (thus indicating a “z” quantity of objects, where“z” is an integer) stored within a context object database 212. Forexample, if a pointer 214 a points the non-contextual data object 208 rto the synthetic context-based object 204 a, while a pointer 216 apoints the context object 210 x to the synthetic context-based object204 a, thus associating the non-contextual data object 208 r and thecontext object 210 x with the synthetic context-based object 204 a(e.g., storing or otherwise associating the data within thenon-contextual data object 208 r and the context object 210 x in thesynthetic context-based object 204 a), the data within thenon-contextual data object 208 r now has been given unambiguous meaningby the data within the context object 210 x. This contextual meaning isthus stored within (or otherwise associated with) the syntheticcontext-based object 204 a.

Similarly, if a pointer 214 b associates data within the non-contextualdata object 208 s with the synthetic context-based object 204 b, whilethe pointer 216 c associates data within the context object 210 z withthe synthetic context-based object 204 b, then the data within thenon-contextual data object 208 s is now given meaning by the data in thecontext object 210 z. This contextual meaning is thus stored within (orotherwise associated with) the synthetic context-based object 204 b.

Note that more than one context object can give meaning to a particularnon-contextual data object. For example, both context object 210 x andcontext object 210 y can point to the synthetic context-based object 204a, thus providing compound context meaning to the non-contextual dataobject 208 r shown in FIG. 2. This compound context meaning providesvarious layers of context to the data in the non-contextual data object208 r.

Note also that while the pointers 214 a-214 b and 216 a-216 c arelogically shown pointing toward one or more of the syntheticcontext-based objects 204 a-204 n, in one embodiment the syntheticcontext-based objects 204 a-204 n actually point to the non-contextualdata objects 208 r-208 t and the context objects 210 x-210 z. That is,in one embodiment the synthetic context-based objects 204 a-204 n locatethe non-contextual data objects 208 r-208 t and the context objects 210x-210 z through the use of the pointers 214 a-214 b and 216 a-216 c.

Consider now an exemplary case depicted in FIG. 3, in which syntheticcontext-based objects are defined for the non-contextual data objectdata “rock”. Standing alone, without any context, the word “rock” ismeaningless, since it is ambiguous and does not provide a reference toany particular subject-matter. That is, “rock” may refer to a stone, orit may be slang for a gemstone such as a diamond, or it may refer to agenre of music, or it may refer to physical oscillation, etc. Thus, eachof these references are within the context of a different subject-matter(e.g., geology, entertainment, physics, etc.).

In the example shown in FIG. 3, then, data (i.e., the word “rock”) fromthe non-contextual data object 308 r is associated with (e.g., stored inor associated by a look-up table, etc.) a synthetic context-based object304 a, which is devoted to the subject-matter “geology”. The data/word“rock” from non-contextual data object 308 r is also associated with asynthetic context-based object 304 b, which is devoted to thesubject-matter “entertainment”. In order to give contextual meaning tothe word “rock” (i.e., define the term “rock”) in the context of“geology”, context object 310 x, which contains the context datum“mineral”, is associated with (e.g., stored in or associated by alook-up table, etc.) the synthetic context-based object 304 a. In oneembodiment, more than one context datum can be associated with a singlesynthetic context-based object. Thus, in the example shown in FIG. 3,the context object 310 y, which contains the datum “gemstone”, is alsoassociated with the synthetic context-based object 304 a.

Associated with the synthetic context-based object 304 b is a contextobject 310 z, which provides the context/datum of “pop music” to theterm “rock” provided by the non-contextual data object 308 r. Thus, thesynthetic context-based object 304 a defines “rock” as that which isrelated to the subject-matter “geology”, including minerals and/orgemstones, while synthetic context-based object 304 b defines “rock” asthat which is related to the subject-matter “entertainment”, includingmusic.

In one embodiment, the data within a non-contextual data object is evenmore meaningless if it is merely a combination of numbers and/orletters. For example, consider the data “104-106” contained within anon-contextual data object 408 r depicted in FIG. 4. Standing alone,without any context, these numbers are meaningless, identify noparticular subject-matter, and thus are completely ambiguous. That is,“104-106” may relate to subject-matter such as a medical condition, aphysics value, a person's age, a quantity of currency, a person'sidentification number, etc. That is, the data “104-106” is sovague/meaningless that the data does not even identify the units thatthe term describes, much less the context of these units.

In the example shown in FIG. 4, then, data (i.e., the term/values“104-106”) from the non-contextual data object 408 r is associated with(e.g., stored in or associated by a look-up table, etc.) a syntheticcontext-based object 404 a, which is devoted to the subject-matter“hypertension”. The term/values “104-106” from non-contextual dataobject 408 r is also associated with a synthetic context-based object404 b, which is devoted to the subject-matter “human fever” and asynthetic context-based object 404 n, which is devoted to thesubject-matter “deep oceanography”. In order to give contextual meaningto the term/values “104-106” (i.e., define the term/values “104-106”) inthe context of “hypertension”, context object 410 x, which contains thecontext data “millimeters of mercury” and “diastolic blood pressure”” isassociated with (e.g., stored in or associated by a look-up table, etc.)the synthetic context-based object 404 a. Thus, multiple context datacan provide not only the scale/units (millimeters of mercury) context ofthe values “104-106”, but the data can also provide the context data“diastolic blood pressure” needed to identify the subject-matter(hypertension) of the synthetic context-based object 404 a.

Associated with the synthetic context-based object 404 b is a contextobject 410 y, which provides the context data of “degrees on theFahrenheit scale” and “human” to the term/values “104-106” provided bythe non-contextual data object 408 r. Thus, the synthetic context-basedobject 404 b now defines term/values “104-106” as that which is relatedto the subject matter of “human fever”. Similarly, associated with thesynthetic context-based object 404 n is a context object 410 z, whichprovides the context data of “atmospheres” to the term/values “104-106”provided by the non-contextual data object 408 r. In this case, thegenerator of the synthetic context-based object database 202 determinesthat high numbers of atmospheres are used to define deep oceanpressures. Thus, the synthetic context-based object 404 n now definesterm/values “104-106” as that which is related to the subject matter of“deep oceanography”.

In one embodiment, the non-contextual data object may provide enoughself-context to identify what the datum is, but not what it means and/oris used for. For example, consider the datum “statin” contained withinthe non-contextual data object 508 r shown in FIG. 5. In the exampleshown in FIG. 5, datum (i.e., the term “statin”) from the non-contextualdata object 508 r is associated with (e.g., stored in or associated by alook-up table, etc.) a synthetic context-based object 504 a, which isdevoted to the subject-matter “cardiology”. The term “statin” fromnon-contextual data object 508 r is also associated with a syntheticcontext-based object 504 b, which is devoted to the subject-matter“nutrition” and a synthetic context-based object 504 n, which is devotedto the subject-matter “tissue inflammation”. In order to give contextualmeaning to the term “statin” (i.e., define the term “statin”) in thecontext of “cardiology”, context object 510 x, which contains thecontext data “cholesterol reducer” is associated with (e.g., stored inor associated by a look-up table, etc.) the synthetic context-basedobject 504 a. Thus, the datum “cholesterol reducer” from context object510 x provides the context to understand that “statin” is used in thecontext of the subject-matter “cardiology”.

Associated with the synthetic context-based object 504 b is a contextobject 510 y, which provides the context/datum of “antioxidant” to theterm “statin” provided by the non-contextual data object 508 r. That is,a statin has properties both as a cholesterol reducer as well as anantioxidant. Thus, a statin can be considered in the context of reducingcholesterol (i.e., as described by the subject-matter of syntheticcontext-based object 504 a), or it may considered in the context ofbeing an antioxidant (i.e., as related to the subject-matter ofsynthetic context-based object 504 b). Similarly, a statin can also bean anti-inflammatory medicine. Thus, associated with the syntheticcontext-based object 504 n is the context object 510 z, which providesthe context data of “anti-inflammatory medication” to the term “statin”provided by the non-contextual data object 508 r. This combinationidentifies the subject-matter of the synthetic context-based object 504n as “tissue inflammation”.

Once the synthetic context-based objects are defined, they can be linkedto data stores. A data store is defined as a data repository of a set ofintegrated data, such as text files, video files, webpages, etc. Withreference now to FIG. 6, a process for associating one or more datastores with specific synthetic context-based objects in a system 600 ispresented. Note that system 600 is a processing and storage logic foundin computer 102 and/or data storage system 152 shown in FIG. 1, whichprocess, support, and/or contain the databases, pointers, and objectsdepicted in FIG. 6. The data structure 604 is a database of multipledata stores 602 m-602 p (thus indicating a “p” number of data stores,where “p” is an integer), which may be text documents, hierarchicalfiles, tuples, object oriented database stores, spreadsheet cells,uniform resource locators (URLs), etc.

That is, in one embodiment, the data structure 604 is a database of textdocuments (represented by one or more of the data stores 602 m-602 p),such as journal articles, webpage articles, electronically-storedbusiness/medical/operational notes, etc.

In one embodiment, the data structure 604 is a database of text, audio,video, multimedia, etc. files (represented by one or more of the datastores 602 m-602 p) that are stored in a hierarchical manner, such as ina tree diagram, a lightweight directory access protocol (LDAP) folder,etc.

In one embodiment, the data structure 604 is a relational database,which is a collection of data items organized through a set of formallydescribed tables. A table is made up of one or more rows, known as“tuples”. Each of the tuples (represented by one or more of the datastores 602 m-602 p) share common attributes, which in the table aredescribed by column headings. Each tuple also includes a key, which maybe a primary key or a foreign key. A primary key is an identifier (e.g.,a letter, number, symbol, etc.) that is stored in a first data cell of alocal tuple. A foreign key is typically identical to the primary key,except that it is stored in a first data cell of a remote tuple, thusallowing the local tuple to be logically linked to the foreign tuple.

In one embodiment, the data structure 604 is an object orienteddatabase, which stores objects (represented by one or more of the datastores 602 m-602 p). As understood by those skilled in the art ofcomputer software, an object contains both attributes, which are data(i.e., integers, strings, real numbers, references to another object,etc.), as well as methods, which are similar to procedures/functions,and which define the behavior of the object. Thus, the object orienteddatabase contains both executable code and data.

In one embodiment, the data structure 604 is a spreadsheet, which ismade up of rows and columns of cells (represented by one or more of thedata stores 602 m-602 p). Each cell (represented by one or more of thedata stores 602 m-602 p) contains numeric or text data, or a formula tocalculate a value based on the content of one or more of the other cellsin the spreadsheet.

In one embodiment, the data structure 604 is a collection of universalresource locators (URLs) for identifying a webpage, in which each URL(or a collection of URLs) is represented by one or more of the datastores 602 m-602 p.

These described types of data stores are exemplary, and are not to beconstrued as limiting what types of data stores are found within datastructure 604.

Note that the data structure 604 is homogenous in one embodiment, whiledata structure 604 is heterogeneous in another embodiment. For example,assume in a first example that data structure 604 is a relationaldatabase, and all of the data stores 602 m-602 p are tuples. In thisfirst example, data structure 604 is homogenous, since all of the datastores 602 m-602 p are of the same type. However, assume in a secondexample that data store 602 m is a text document, data store 602 n is anMM image, data store 602 p is a tuple from a relational database, etc.In this second example, data structure 604 is a heterogeneous datastructure, since it contains data stores that are of different formats.

FIG. 6 thus represents various data stores being “laid over” one or moreof the synthetic context-based objects 304 a-304 n described above inFIG. 3. That is, one or more of the data stores 602 m-602 p is mapped toa particular synthetic context-based object from the syntheticcontext-based objects 304 a-304 n, in order to facilitateexploring/searching the data structure 604. For example, a pointer 606(e.g., an identifier located within both synthetic context-based object304 a and data store 602 m) points the data store 602 m to the syntheticcontext-based object 304 a, based on the fact that the data store 602 mcontains data found in the non-contextual data object 208 r and thecontext object 210 x, which together gave the subject-matter meaning tothe synthetic context-based object 304 a as described above. Similarly,pointer 608 points data store 602 n to synthetic context-based object304 a as well, provided that synthetic context based object 304 a alsocontains data from context object 210 y, as described in an alternateembodiment above. Similarly, pointer 610 points data store 602 p tosynthetic context-based object 304 b, since data store 602 p andsynthetic context-based object 304 b both contain data from thenon-contextual data object 208 r as well as the context object 210 z.

As described in FIG. 6, the pointers enable various data stores to beassociated with subject-matter-specific synthetic context based objects.This association facilitates searching the data structure 604 accordingto the subject-matter, which is defined by the combination of data fromthe non-contextual data object and the context object, of a particularsynthetic context-based object. Thus, as depicted in FIG. 7, anexemplary process for locating a particular data store via a particularsynthetic context-based object is presented.

Assume that a user is using a computer such as requesting computer 702,which may be the user computer 154 shown in FIG. 1. The requestingcomputer 702 sends a request 704 to synthetic context-based object 304 aif the user desires information about geological rocks (i.e., thesubject-matter of geology). The user can specify this particularcontext-based object 304 a by manually choosing it from a displayedselection of synthetic context-based objects, or logic (e.g., part ofSCBOPL 148 shown in FIG. 1) can determine which synthetic context-basedobject and/or subject-matter are appropriate for a particular user,based on that user's interests, job description, job title, etc. Thesynthetic context-based object then uses pointer 606 to point to datastore 602 m and/or pointer 608 to point to data store 602 n, and returnsthe data stored within these data stores to the requesting computer 702.Thus, the user/requesting system does not have to perform a search ofall of the data structure 604, using data mining and associative logic,in order to find the data that the user desires. Rather, making anassociation between the user and a particular synthetic context-basedobject provides a rapid gateway from the requesting computer 702 to thedesired data store.

Similarly, if the requester sends a request 706 to the syntheticcontext-based object 304 b, then data from the data store 602 pregarding rock music is retrieved and sent to the requester 702.

Note that the context objects described herein (e.g., context objects210 x-210 z shown in FIG. 2) are defined/created based on constraintsand/or hierarchical values in one embodiment. For example, consider thecontext object 310 z from FIG. 3, which is presented in additionaldetail in FIG. 8. For example, assume that a base context object 802provides the context of “music”, which will ultimately provide part ofthe context for context object 310 z (“Pop music”) depicted in FIG. 3.However, additional sub-context objects are also available to furtherdefine the base context object 802. One example of such sub-contextobjects include sub-context objects 804 a-804 c (which define aparticular decade from which the music was firstperformed/recorded/released). Another exemplary sub-context object issub-context object 806, which provides the descriptor “operatic”, whichprovides the context for a “rock opera” (rather than “grand opera”,“light opera”, etc.). Another exemplary sub-context object issub-context object 808, which provides the descriptor “hip hop”, whichmay be a sub-genre of rock music. Similarly, sub-context object 810provides the descriptor “indie”, indicating that the music is from anindependent record label, rather than a major recording label (e.g., arecording company that has been predefined as a “major” recordingcompany). Similarly, sub-context object 812 provides the descriptor“mash-up”, indicating that the music is a combination of two types ofmusic (e.g., spoken word and soft rock). Similarly, sub-context object814 provides the descriptor “video”, indicating that the file is a musicvideo, rather than an audio-only recording.

As depicted in FIG. 8, the context object 310 z is created using varioussub-context objects that establish a scope and bound (i.e., contextualand bounded range) of the context object. That is, in the example shown,context object 310 z describes a context of music that is from the1980's, includes a mash-up with hip-hop, and is a music video. Note thatsub-context objects 804 a, 804 b, and 810 may or may not be part ofcontext object 310 z in one embodiment (as indicated by the dashedlines). However, the context object 310 z expressly excludes music filesthat are “rock operas”, as indicated by the “X” blocking a connectorfrom element 802 to element 806. Thus, when searching for related files(see FIG. 7), only those data stores that include the sub-contextobjects for a particular context object (as described in FIG. 8) will beretrieved.

While the context object can be defined according to certain sub-contextobjects, as depicted in FIG. 8, in one embodiment the context objectselected is according to a hierarchical arrangement, which may beweighted. For example, consider the context objects 510 x-510 z depictedin FIG. 5. All of these are medical-based. In order to know which of thecontext objects is to be applied to the non-contextual data object 508r, a hierarchy can be established in one embodiment. For example, assumethat context object 510 x is predetermined to be a morelikely/useful/common context for the non-contextual data object 508 rthan context objects 510 y or 510 z. In this example, context object 510x is applied to non-contextual data object 508 r, while ignoring contextobjects 510 y and 510 z. Thus, only data files related to “cardiology”(according to the synthetic context-based object 504 a) will be searchedfor and retrieved (as described in FIG. 7). In another embodiment, thepredefined ranking of the context objects 510 x-510 z result in asequential search pattern. For example, assume that context object 510 xis ranked higher (and/or given a higher weighting) than context object510 y, and that context object 510 y is ranked/weighted higher thancontext object 510 z. In this example, data that matches syntheticcontext-based object 504 a is searched/retrieved first, followed bysearching for and retrieving data that matches synthetic context-basedobject 504 b, followed by searching for and retrieving data that matchessynthetic context-based object 504 n.

With reference now to FIG. 9, a high-level flow chart of one or moresteps performed by a computer processor to generate and utilizesynthetic context-based objects to locate and/or return specific datastores to a requester is presented. After initiator block 900, a contextobject is defined based on predefined constraints (block 902), asdescribed in FIG. 8 and/or as described herein with reference tohierarchical constraints imposed on the exemplary context objectsdepicted in FIG. 5.

A non-contextual data object is then associated with the context objectto define a synthetic context-based object (block 904). As describedherein, the non-contextual data object ambiguously relates to multiplesubject-matters. Standing alone, it is unclear to which of thesemultiple-subject matters the data in the non-contextual data object isdirected. However, the context object provides a context that identifiesa specific subject-matter, from the multiple subject-matters, of thenon-contextual data object.

As described in block 906, the synthetic context-based object isassociated with at least one specific data store. This at least onespecific data store contains data that is associated with data containedin the non-contextual data object and the context object. That is, thedata in the data store may be identical to that found in thenon-contextual data object and the context object (i.e., the terms“rock” and “mineral” are in both the data store as well as therespective non-contextual data object and context object); it may besynonymous to that found in the non-contextual data object and thecontext object (i.e., the terms “rock” and “mineral” are the respectivenon-contextual data object and context object while synonyms “stone” and“element” are in the data store); and/or it may simply be deemed relatedby virtue of a lookup table that has been previously created (i.e., theterm “rock” is mapped to the term “stone” and/or the term “mineral” ismapped to the term “elements” in a lookup table or similar associativedata structure).

In one embodiment, the terms in the data stores are identified by datamining a data structure in order to locate the data from thenon-contextual data object and the context object in one or more datastores. Thus, this data mining locates at least one specific data storethat contains data contained in the non-contextual data object and thecontext object.

In one embodiment, the data store is a text document. In thisembodiment, the data mining entails searching the text document for textdata that is part of the synthetic context-based object, and thenassociating the text document that contains this text data with thesynthetic context-based object.

In one embodiment, the data store is a video file. In this embodiment,the data mining entails searching metadata associated with the videofile for text data that is part of the synthetic context-based object,and then associating the video file having this metadata with thesynthetic context-based object.

In one embodiment, the data store is a web page. In this embodiment, thedata mining entails searching the web page for text data that is part ofthe synthetic context-based object, and then associating the web pagethat contains this text data with the synthetic context-based object.

Note that in one embodiment, the specific subject-matter for aparticular data store in the data structure is exclusive to only thatparticular data store. That is, only one data store is mapped to aparticular synthetic context-based object, such that there is aone-to-one relationship between each synthetic context-based object andeach data store. Note further that in another embodiment, the specificsubject-matter for a particular data store in the data structureoverlaps at least one other data store. That is, multiple data storesare mapped to a particular synthetic context-based object, such thatthere is a one-to-many relationship between a particular syntheticcontext-based object and multiple data stores.

With reference now to block 908, a request for any data store that isassociated with the synthetic context-based object is then received(e.g., by computer 102 shown in FIG. 1). In one embodiment, this requestis received from the requester via a request pointer, which points to aspecific synthetic context-based object. In one embodiment, thisspecific synthetic context-based object is user-selected and/oruser-specified (i.e., the user either manually chooses which syntheticcontext-based object is to be used, or this choice is made by processinglogic based on characteristics of the requesting user).

As described in block 910, at least one data store that is associatedwith the synthetic context-based object is then returned to therequester. The process ends at terminator block 912.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present disclosure. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the presentinvention. As used herein, the singular forms “a”, “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“comprises” and/or “comprising,” when used in this specification,specify the presence of stated features, integers, steps, operations,elements, and/or components, but do not preclude the presence oraddition of one or more other features, integers, steps, operations,elements, components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of various embodiments of the present invention has beenpresented for purposes of illustration and description, but is notintended to be exhaustive or limited to the present invention in theform disclosed. Many modifications and variations will be apparent tothose of ordinary skill in the art without departing from the scope andspirit of the present invention. The embodiment was chosen and describedin order to best explain the principles of the present invention and thepractical application, and to enable others of ordinary skill in the artto understand the present invention for various embodiments with variousmodifications as are suited to the particular use contemplated.

Note further that any methods described in the present disclosure may beimplemented through the use of a VHDL (VHSIC Hardware DescriptionLanguage) program and a VHDL chip. VHDL is an exemplary design-entrylanguage for Field Programmable Gate Arrays (FPGAs), ApplicationSpecific Integrated Circuits (ASICs), and other similar electronicdevices. Thus, any software-implemented method described herein may beemulated by a hardware-based VHDL program, which is then applied to aVHDL chip, such as a FPGA.

Having thus described embodiments of the present invention of thepresent application in detail and by reference to illustrativeembodiments thereof, it will be apparent that modifications andvariations are possible without departing from the scope of the presentinvention defined in the appended claims.

What is claimed is:
 1. A method for generating and utilizing syntheticcontext-based objects, the method comprising: defining, by one or moreprocessors, a context object, wherein the context object provides acontext that identifies a specific subject-matter, from multiplesubject-matters, of a non-contextual data object, and wherein thenon-contextual data object ambiguously relates to one or more of themultiple subject-matters; associating, by one or more processors, thenon-contextual data object with the context object to define a syntheticcontext-based object; associating, by one or more processors, thesynthetic context-based object with at least one specific data store,wherein said at least one specific data store is a data repository ofdata that is relevant to a context of the synthetic context-basedobject, and wherein the specific subject-matter for said at least onespecific data store in a data structure overlaps a subject-matter ofanother data store in the data structure; receiving, from a requester, arequest for data from said at least one specific data store that isassociated with the synthetic context-based object, wherein said atleast one specific data store is within a database of multiple datastores; and returning, to the requester, data from said at least onespecific data store that is associated with the synthetic context-basedobject.
 2. The method of claim 1, further comprising: data mining, byone or more processors, the data structure for the non-contextual dataobject and the context object, wherein said data mining locates said atleast one specific data store that comprises data contained in both thenon-contextual data object and the context object.
 3. The method ofclaim 1, wherein the specific subject-matter for a particular data storein the data structure is exclusive to only said particular data store,and wherein said particular data store is mapped only to the syntheticcontext-based object such that there is a one-to-one relationshipbetween the synthetic context-based object and said particular datastore.
 4. The method of claim 1, wherein said at least one specific datastore is a text document, and wherein the method further comprises:searching, by one or more processors, the text document for text datathat is part of the synthetic context-based object; and associating thetext document that contains said text data with the syntheticcontext-based object.
 5. The method of claim 1, wherein said at leastone specific data store is a video file, and wherein the method furthercomprises: searching, by one or more processors, metadata associatedwith the video file for text data that is part of the syntheticcontext-based object; and associating the video file having saidmetadata with the synthetic context-based object.
 6. The method of claim1, wherein said at least one specific data store is a web page, andwherein the method further comprises: searching, by one or moreprocessors, the web page for text data that is part of the syntheticcontext-based object; and associating the web page that contains saidtext data with the synthetic context-based object.
 7. The method ofclaim 1, further comprising: receiving the request from the requestervia a request pointer, wherein the request pointer points to auser-specified synthetic context-based object.
 8. The method of claim 1,wherein said at least one specific data store is a set of objects thatinclude object oriented programming (OOP) attributes and OOP methods,wherein the OOP attributes are from a group consisting of integers,strings, real numbers, and references to another object, etc., whereinthe OOP methods are functions that define a behavior of an object, andwherein the method further comprises: retrieving, by one or moreprocessors, an object from said at least one specific data store that isrelevant to the synthetic context-based object; and executing, by one ormore processors, the retrieved object.
 9. The method of claim 1, whereinsaid at least one specific data store is a relational database, whereinthe relational database is a collection of data items organized througha set of formally described tables, wherein a table is composed of oneor more rows, wherein each row from the one or more rows is a tuple thatshares a common attribute, wherein a foreign key is stored in a firsttuple in the relational database, wherein the foreign key is anidentifier of a second tuple in the relational database, wherein thesecond tuple is said at least one specific data store, and wherein themethod further comprises: associating, by one or more processors, theforeign key with the synthetic context-based object and said at leastone specific data store; retrieving, by one or more processors, theforeign key from the first tuple; and using, by one or more processors,the foreign key to identify said second tuple in order to retrieve saidat least one specific data store that is associated with the syntheticcontext-based object.
 10. The method of claim 1, wherein the contextobject is from a plurality of context objects used to create syntheticcontext-based objects, and wherein the method further comprises:applying, by one or more processors, a predefined ranking to each of theplurality of context objects used to create synthetic context-basedobjects; and searching, by one or more processors, the data repositoryfor synthetic context-based objects in order of the predefined rankingof context objects used to create the synthetic context-based objects.11. The method of claim 1, further comprising: in response to receivingthe request for data, returning, by one or more processors, the multipledata stores to the requester.
 12. The method of claim 1, wherein thedatabase of multiple data stores contains heterogeneous data structures,wherein the heterogeneous data structures include a text document, amedical image file, and a tuple from a relational database.
 13. Themethod of claim 1, wherein said at least one specific data store is acollection of universal resource locators (URLs) that identify webpages.14. A computer program product for generating and utilizing syntheticcontext-based objects, the computer program product comprising anon-transitory computer readable storage medium having program codeembodied therewith, the program code readable and executable by aprocessor to perform a method comprising: defining a context object,wherein the context object provides a context that identifies a specificsubject-matter, from multiple subject-matters, of a non-contextual dataobject, and wherein the non-contextual data object ambiguously relatesto one or more of the multiple subject-matters; associating thenon-contextual data object with the context object to define a syntheticcontext-based object; associating the synthetic context-based objectwith at least one specific data store, wherein said at least onespecific data store is a data repository of data that is relevant to acontext of the synthetic context-based object, and wherein the specificsubject-matter for said at least one specific data store in a datastructure overlaps a subject-matter of another data store in the datastructure; receiving, from a requester, a request for data from said atleast one specific data store that is associated with the syntheticcontext-based object, wherein said at least one specific data store iswithin a database of multiple data stores; and returning, to therequester, data from said at least one specific data store that isassociated with the synthetic context-based object.
 15. The computerprogram product of claim 14, wherein the method further comprises: datamining the data structure for the non-contextual data object and thecontext object, wherein said data mining locates said at least onespecific data store that comprises data contained in both thenon-contextual data object and the context object.
 16. The computerprogram product of claim 14, wherein the specific subject-matter for aparticular data store in the data structure is exclusive to only saidparticular data store, and wherein said particular data store is mappedonly to the synthetic context-based object such that there is aone-to-one relationship between the synthetic context-based object andsaid particular data store.
 17. The computer program product of claim14, wherein said at least one specific data store is a relationaldatabase, wherein the relational database is a collection of data itemsorganized through a set of formally described tables, wherein a table iscomposed of one or more rows, wherein each row from the one or more rowsis a tuple that shares a common attribute, wherein a foreign key isstored in a first tuple in the relational database, wherein the foreignkey is an identifier of a second tuple in the relational database,wherein the second tuple is said at least one specific data store, andwherein the method further comprises: associating the foreign key withthe synthetic context-based object and said at least one specific datastore; retrieving the foreign key from the first tuple; and using theforeign key to identify said second tuple in order to retrieve said atleast one specific data store that is associated with the syntheticcontext-based object.
 18. A computer system comprising: one or moreprocessors; one or more computer readable memories; and one or morenon-transitory computer readable storage mediums, wherein programinstructions are stored on at least one of the one or morenon-transitory computer readable storage mediums for execution by atleast one of the one or more processors via at least one of the one ormore computer readable memories to perform a method comprising: defininga context object, wherein the context object provides a context thatidentifies a specific subject-matter, from multiple subject-matters, ofa non-contextual data object, and wherein the non-contextual data objectambiguously relates to one or more of the multiple subject-matters;associating the non-contextual data object with the context object todefine a synthetic context-based object; associating the syntheticcontext-based object with at least one specific data store, wherein saidat least one specific data store is a data repository of data that isrelevant to a context of the synthetic context-based object, and whereinthe specific subject-matter for said at least one specific data store ina data structure overlaps a subject-matter of another data store in thedata structure; receiving, from a requester, a request for data fromsaid at least one specific data store that is associated with thesynthetic context-based object, wherein said at least one specific datastore is within a database of multiple data stores; and returning, tothe requester, data from said at least one specific data store that isassociated with the synthetic context-based object.
 19. The computersystem of claim 18, wherein the method further comprises: data miningthe data structure for the non-contextual data object and the contextobject, wherein said data mining locates said at least one specific datastore that comprises data contained in both the non-contextual dataobject and the context object.
 20. The computer system of claim 18,wherein the specific subject-matter for a particular data store in thedata structure is exclusive to only said particular data store, andwherein said particular data store is mapped only to the syntheticcontext-based object such that there is a one-to-one relationshipbetween the synthetic context-based object and said particular datastore.